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    <identifier>10.57760/sciencedb.08065</identifier>
    <datestamp>2023-04-28T08:05:01Z</datestamp>
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  <dc:date>2023-04-28</dc:date>
  <dc:title>Novel densi-melting effect for ultra-precision laser beam figuring with clustered overlapping technology at full-spatial-frequency</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.08065</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Laser beam figuring (LBF), as a processing technology for ultra-precision figuring, is expected to be a key technology for further improving optics performance. To the best of our knowledge, we firstly demonstrated CO2 LBF for full-spatial-frequency error convergence at negligible stress. We found that controlling the subsidence and surface smoothing caused by material densification and melt under specific parameters range is an effective way to ensure both form error and roughness. Besides, an innovative &amp;ldquo;densi-melting&amp;rdquo; effect is further proposed to reveal the physical mechanism and guide the nano-precision figuring control, and the simulated results at different pulse durations fit well with the experiment results. Plus, to suppress the laser scanning ripples (mid-spatial-frequency (MSF) error) and reduce the control data volume, a novel clustered overlapping processing technology is proposed, where the laser processing in each sub-region is regarded as tool influence function (TIF). Through the overlapping control of TIF figuring depth, we achieved LBF experiments for the form error root mean square (RMS) reduced from 0.009&amp;lambda; to 0.003&amp;lambda; (&amp;lambda;=632.8nm) without destroying microscale roughness (0.447nm to 0.453nm) and nanoscale roughness (0.290nm to 0.269nm). The establishment of the densi-melting effect and the clustered overlapping processing technology prove that LBF provides a new high-precision, low-cost manufacturing method for optics.</dc:description>
  <dc:subject>fused silica; laser beam figuring; tool influence function</dc:subject>
  <dc:creator>Yichi Han</dc:creator>
  <dc:creator>Songlin Wan</dc:creator>
  <dc:creator>Xiaocong Peng</dc:creator>
  <dc:creator>Guochang Jiang</dc:creator>
  <dc:creator>Lin Wang</dc:creator>
  <dc:creator>Chaoyang Wei</dc:creator>
  <dc:creator>Jianda Shao</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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